README
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knn-go
K-Nearest Neighbours library for Golang
Note: This is alpha software at best. I make no guarantees as to the correctness of the implementation, nor to the stability of the API. Use at your own risk.
Sample Usage
Documentation
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Index ¶
Examples ¶
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func CosineDistance ¶
Types ¶
type DistanceFn ¶
type NaiveKNN ¶
type NaiveKNN struct {
// contains filtered or unexported fields
}
Example ¶
// Define the input vectors
vecs := []Vector{
{ID: "vec1", Point: []float64{1.0, 2.0, 3.0}},
{ID: "vec2", Point: []float64{4.0, 5.0, 6.0}},
{ID: "vec3", Point: []float64{7.0, 8.0, 9.0}},
}
// Create a new NaiveKNN instance
knn, err := NewNaiveKNN(vecs, CosineDistance)
if err != nil {
fmt.Println("Failed to create NaiveKNN:", err)
return
}
// Define the target vector
target := Vector{ID: "target", Point: []float64{1., 5., 9.}}
// Perform the KNN search
k := 2
result := knn.Search(k, target)
// Print the result
for _, vec := range result {
fmt.Println(vec.ID, vec.Point)
}
Output: vec1 [1 2 3] vec2 [4 5 6]
func NewNaiveKNN ¶
func NewNaiveKNN(vecs []Vector, fn DistanceFn) (*NaiveKNN, error)
Source Files
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